Overinflated hype about “where the puck is going” being wrong is…not a new phenomenon. And the non-tech media (traditional and social, and particularly a whole lot of the elite commentariat that spans both more than the “hard” news side of traditional media, though that is influenced too) perspective on this is driven quite disproportionately by the marketing message of the narrow set of people with the most financial stake in promoting the hype. Even the cautionary notes being sounded there are exactly the ones that are being used by the same people to promote narrow control.

The part that gets me is they aren't just aimlessly making posts, they're getting involved with webinars targeted at educators in their respective topics, speaking at regional events about the future with ChatGPT, etc.

One of them was a really excellent teacher but like this dude absolutely does not have any qualifications to be speaking on ChatGPT, and I hope it hasn't actually changed his teaching style too much because I'm having trouble imagining how ChatGPT could've fit in well with the way he used to teach.

Don't get me wrong, hype often surrounds something legitimately good, but I think ChatGPT is being taken way out of context in both the ML achievement it is and in what things the tool is actually useful for. I guess it is easy for a layperson to make mistaken assumptions about where the puck is going when they see what ChatGPT can do.

[1] "The story took place in 1929: Joseph Patrick Kennedy Sr., JFK's father, claimed that he knew it was time to get out of the stock market when he got investment tips from a shoeshine boy."

I grew up and using a pocket calculator was verboten. You just did not do it. You better learn and memorize all of that stuff. Spin on 10 years after me and all kids have them now. If you have the right app on your phone the thing will OCR the problem and auto solve it and show you the steps. ChatGPT and its ilk are here, now. How we learn and create things has dramatically changed in under a year. It is not clear how much though.

Teachers are trying to get ahold of what does it mean to teach if you can just ask some device to summarize something as complex as the interactions of the 6 major countries in WWII and what caused it. Then the thing thinks for 2 seconds and spits out a 1000 word essay on exactly that. Then depending on which one you use it will footnote it all and everything.

This style of learning is going to take some getting used to. This tool is in their classrooms right now. Right or wrong. It will be there. The teachers are going to have to figure out what this means to their class planning. Not 5 years from now, today.

These posts ooze hype bullshit, not nuanced talk about pros and cons and how it will affect education. ChatGPT should be thought of as a writing tool and perhaps an information source on very surface level topics. Trying to teach an advanced research course at a top school with ChatGPT heavily involved is a terrible idea on the other hand.

I have tested asking it about a number of specific topics in biology research/asking questions about particular papers, and it gives horrible answers the majority of the time. If someone submitted that as a paper to me I'd give it a bad grade because it is dumb, I wouldn't need to know if it were ChatGPT or not. I would be alarmed if my kid's teacher went from organically teaching how to dissect a scientific paper to suggesting that a major part of the curriculum can be replaced with talking to GPT.

I've seen articles about teachers taking the other extreme against ChatGPT too, but I haven't personally seen anything that was a realistic take on what LLMs can do. Maybe it boils down again to disagreement on "where the puck is going" but to me most of the hype is making ridiculous assumptions about what is imminent meanwhile ignoring the things worth discussing now.

Which sounds a lot like bubbles. The dot com crash didn't mean the internet was a bad idea or that it wasn't worth discussing at that time.

"where the puck is going" is something to consider and we will 100% get that wrong, but right now this thing is creating waves and making issues now.

Already happening. A student in Russia submitted his thesis written with the help of GPT, it was accepted, then rejected, then accepted: https://www.themoscowtimes.com/2023/02/02/russian-student-al...

In any event, he isn't concerned at all about students using it for assignments, it's the degree to which he seems to think it can be integrated in his current curriculum that alarms me. I think he is misunderstanding the capabilities and therefore pitching something that doesn't actually make sense.

The other teacher I didn't follow as closely, I just got a kick out of seeing she was now advertising some sort of webinar about ChatGPT filled with buzzwords too.

Also if a teacher is really serious about wanting to plan around what GPT can and can't do to the point they want to be a teaching authority on it, they should be consulting with people in the relevant domain. When I want to use a new tool in the lab I talk with colleagues that have a great deal of relevant experience before I start working it into experiments. I can't imagine starting to give advice to others on the matter when I don't actually know the current nuances.

And seriously, how many people were actually saying “WolframAlpha will destroy a huge amount of programming jobs”?

But it looks like an exponentially steep climb from here. indefinitely

Maybe superintelligence isn't possible for some reason, but the fact we exist should tell you that general intelligence is not magic.

Though I think that it's more likely that I'll become shaman who talks to the spirits. Managers hate computers and they'd prefer to pay someone to deal with them.

That rapid progression can be modeled with an exponential growth curve, like Moore’s law, even though nothing material can have a sustained exponential growth. Regardless of how the curve is modeled, the steepness is such that it serves as a step function in evolution.

With that clarified, there is first the question of “is the technological progression going to level off soon?” And I think the answer is no. The second question is, “how are we going to deal?” And the answer to that question can only be addressed once we answer the question: “what kind of world do we want to live in?”

People generally use the term to mean the point at which progress is automatic, unbounded, and instant. E.g. AIs that can produce smarter AIs themselves, in short order.

I’m not a singularity believer (singularitist?); from the perspective of 1000 years ago we’re already at the point of infinite progress in zero time. I think individuals, the culture, and the species adapt to accelerating progress, and I intuit, maybe wrongly, that Gödel‘s theorem means that technology will never become runaway and recursive.

But I think that’s what people mean, more than just a step/paradigm change like the internet.

Additionally, "the rate of increase in capabilities" is very much a false flag. Past performance (especially for second-order things like 'rate of improvement') is an absolute batshit insane metric for predicting future success.

https://russellinvestments.com/us/blog/past-performance-no-g...

The advancements have eaten low hanging fruit. Once all the low hanging fruit is gone, we'll all realize GPT will never be tall enough to reach the good stuff.

But the history of technology says that demand is recursive; the more tech produced, the more demand there is for producers.

There may be a time when we hit the old “the whole world only needs 5 computers”[0] limit, but I don’t think we’re anywhere close. AI is providing leverage to create net more programming; it is not replacing programmers in a zero sum game.

0. https://www.theguardian.com/technology/2008/feb/21/computing...

> In economics, the lump of labour fallacy is the misconception that there is a fixed amount of work—a lump of labour—to be done within an economy which can be distributed to create more or fewer jobs.

This is a very bold claim IMO.

Modeling/understanding interactions in a complex system of potential black boxes is much, much more computationally difficult problem that source code to source code operations.